Atomwise Enters Three Joint Ventures to Use AI Platform for Drug Development

It’s been an incredibly busy week so far for San Francisco-based Atomwise, a company focused on using artificial intelligence (AI) for drug discovery. The company has signed three deals this week and it’s only Wednesday.

It’s been an incredibly busy week so far for San Francisco-based Atomwise, a company focused on using artificial intelligence (AI) for drug discovery. The company has signed three deals this week and it’s only Wednesday.

On Tuesday, the company launched a joint venture with Cleveland-based OncoStatyx. OncoStatyx is a preclinical-stage oncology company. The joint venture will work to discover and develop small molecule drugs that inhibit KDM5B, a key epigenetic modulator protein in triple-negative breast cancer ITNBC).

Atomwise will utilize its AI tech platform to model interactions between the KDM5B drug targets and potential inhibitors. OncoStatyx will provide proprietary data about the interactions between the target and various lead compounds.

“As an academic researcher it’s very gratifying to see the translation of my lab’s work on tumor suppressor HEXIM1 into potential clinical medicines,” stated Monica Montano, professor of Pharmacology at Case Western School of Medicine and chief scientific officer and co-founder of OncoStatyx. “We are planning to develop the first medicine to induce the expression of a tumor suppressor as the primary therapeutic approach to treat solid tumor cancers. I’m very interested to see what emerges from the collaboration between Atomwise and OncoStatyx, certainly things will move a lot more quickly now with access to Atomwise’s expertise.”

Also on September 10, Atomwise signed a joint venture with Seattle’s SEngine Precision Medicine to advance novel oncology drug discovery. SEngine Precision Medicine will offer validated gene targets necessary for the growth of mutant cancer cells. Atomwise will use its AI platform to discover and develop inhibitors against those targets. SEngine will use its PARIS Test to conduct “in vitro clinical trials” to screen candidate drugs and combinations against living tumors in patient-derived organoids.

“The combined capabilities of this collaboration create a model for the next generation of drug discovery to decrease time to market and lower the cost of clinical trials,” said Carla Grandori, founder and chief executive officer of SEngine.

On September 11, Atomwise launched a joint venture with Belmont, California-based Atropos Therapeutics. Atropos calls itself a senescence platform discovery company. Cellular senescence is a biological mechanism where cells stop dividing irreversibly—it’s a normal part of aging. However, when the senescence mechanisms malfunction, it plays a role in cancer development. Drugs that modulate senescence have potential as anticancer drugs.

The two companies will use their complementary capabilities to screen molecules for undisclosed targets that modulate cellular senescence.

“This partnership with Atropos is an opportunity to ultimately provide patients with a fundamentally different class of drugs,” said Abraham Heifets, chief executive officer and co-founder of Atomwise. “We are excited to apply our technology to targets that are considered to be intractable and advance the discovery and development of drugs that modulate cellular senescence to treat cancer.”

The last year or two has marked dramatically increased interest on the part of biopharma in AI. One of the most recent stories was Hong Kong-based Insilico Medicine developing GENTRL, an AI system for drug discovery.

In its tests, GENTRL was able to “ideate and generate” a new molecule from beginning to end in 21 days—six molecules, in fact. In a more surprising move, Insilico has made GENTRL’s source code available as open source. GENTRL stands for general tensorial reinforcement learning. It has a two-step algorithm that maps and explores new compound structures within the scaffolding of chemical parameters. It then uses a machine learning model to “learn” DDR1 and common kinase inhibitors.

In May, AstraZeneca announced a long-term collaboration deal with BenevolentAI, a UK-based company focused on combining computational medicine and advanced artificial intelligence. The two companies will focus on using AI and machine learning to discover and develop new drugs for chronic kidney disease (CKD) and idiopathic pulmonary fibrosis (IPF).

In early April, only a few weeks after Concerto HealthAI inked a deal with Bristol-Myers Squibb, it signed a similar deal with Pfizer. The commonality was Concerto focuses on oncology-specific Real-World Data (RWD) and advanced AI for Real-World Evidence (RWE) generation, an area of increasing interest for biopharma companies.

In March 2019, Oxford Biomedica announced it had inked a two-year R&D collaboration with Microsoft Research. The goal is to improve the yield and quality of next-generation gene therapy vectors—typically viruses—using AI and machine learning.

And those are just a few of the most recent collaborations.

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